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Refinado por: assunto: Life Sciences & Biomedicine remover
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iCircDA-MF: identification of circRNA-disease associations based on matrix factorization
iCircDA-MF: identification of circRNA-disease associations based on matrix factorization
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iCircDA-MF: identification of circRNA-disease associations based on matrix factorization

Wei, Hang ; Liu, Bin

Briefings in bioinformatics, 2020-07, Vol.21 (4), p.1356-1367 [Periódico revisado por pares]

England: Oxford University Press

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Repurposing High-Throughput Image Assays Enables Biological Activity Prediction for Drug Discovery
Repurposing High-Throughput Image Assays Enables Biological Activity Prediction for Drug Discovery
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Repurposing High-Throughput Image Assays Enables Biological Activity Prediction for Drug Discovery

Simm, Jaak ; Klambauer, Günter ; Arany, Adam ; Steijaert, Marvin ; Wegner, Jörg Kurt ; Gustin, Emmanuel ; Chupakhin, Vladimir ; Chong, Yolanda T. ; Vialard, Jorge ; Buijnsters, Peter ; Velter, Ingrid ; Vapirev, Alexander ; Singh, Shantanu ; Carpenter, Anne E. ; Wuyts, Roel ; Hochreiter, Sepp ; Moreau, Yves ; Ceulemans, Hugo

Cell chemical biology, 2018-05, Vol.25 (5), p.611-618.e3 [Periódico revisado por pares]

Elsevier Ltd

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3
Predicting drug-disease associations by using similarity constrained matrix factorization
Predicting drug-disease associations by using similarity constrained matrix factorization
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Predicting drug-disease associations by using similarity constrained matrix factorization

Zhang, Wen ; Yue, Xiang ; Lin, Weiran ; Wu, Wenjian ; Liu, Ruoqi ; Huang, Feng ; Liu, Feng

BMC bioinformatics, 2018-06, Vol.19 (1), p.233-233, Article 233 [Periódico revisado por pares]

England: BioMed Central Ltd

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4
Predicting metabolite–disease associations based on auto-encoder and non-negative matrix factorization
Predicting metabolite–disease associations based on auto-encoder and non-negative matrix factorization
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Predicting metabolite–disease associations based on auto-encoder and non-negative matrix factorization

Gao, Hongyan ; Sun, Jianqiang ; Wang, Yukun ; Lu, Yuer ; Liu, Liyu ; Zhao, Qi ; Shuai, Jianwei

Briefings in bioinformatics, 2023-09, Vol.24 (5) [Periódico revisado por pares]

England: Oxford University Press

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5
Machine learning in the prediction of cancer therapy
Machine learning in the prediction of cancer therapy
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Machine learning in the prediction of cancer therapy

Rafique, Raihan ; Islam, S.M. Riazul ; Kazi, Julhash U.

Computational and structural biotechnology journal, 2021-01, Vol.19, p.4003-4017 [Periódico revisado por pares]

Elsevier B.V

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6
Blind source separation for groundwater pressure analysis based on nonnegative matrix factorization
Blind source separation for groundwater pressure analysis based on nonnegative matrix factorization
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Blind source separation for groundwater pressure analysis based on nonnegative matrix factorization

Alexandrov, Boian S. ; Vesselinov, Velimir V.

Water resources research, 2014-09, Vol.50 (9), p.7332-7347 [Periódico revisado por pares]

Washington: Blackwell Publishing Ltd

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7
Pollution characteristics, risk assessment, and source apportionment of heavy metals in road dust in Beijing, China
Pollution characteristics, risk assessment, and source apportionment of heavy metals in road dust in Beijing, China
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Pollution characteristics, risk assessment, and source apportionment of heavy metals in road dust in Beijing, China

Men, Cong ; Liu, Ruimin ; Xu, Fei ; Wang, Qingrui ; Guo, Lijia ; Shen, Zhenyao

The Science of the total environment, 2018-01, Vol.612, p.138-147 [Periódico revisado por pares]

Netherlands: Elsevier B.V

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8
Spatial distribution and source apportionment of heavy metals in soil from a typical county-level city of Guangdong Province, China
Spatial distribution and source apportionment of heavy metals in soil from a typical county-level city of Guangdong Province, China
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Spatial distribution and source apportionment of heavy metals in soil from a typical county-level city of Guangdong Province, China

Wang, Shuo ; Cai, Li-Mei ; Wen, Han-Hui ; Luo, Jie ; Wang, Qiu-Shuang ; Liu, Xie

The Science of the total environment, 2019-03, Vol.655, p.92-101 [Periódico revisado por pares]

Netherlands: Elsevier B.V

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9
Identifying sources and transport routes of heavy metals in soil with different land uses around a smelting site by GIS based PCA and PMF
Identifying sources and transport routes of heavy metals in soil with different land uses around a smelting site by GIS based PCA and PMF
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Identifying sources and transport routes of heavy metals in soil with different land uses around a smelting site by GIS based PCA and PMF

Anaman, Richmond ; Peng, Chi ; Jiang, Zhichao ; Liu, Xu ; Zhou, Ziruo ; Guo, Zhaohui ; Xiao, Xiyuan

The Science of the total environment, 2022-06, Vol.823, p.153759-153759, Article 153759 [Periódico revisado por pares]

Netherlands: Elsevier B.V

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10
Contamination assessment and source apportionment of heavy metals in agricultural soil through the synthesis of PMF and GeogDetector models
Contamination assessment and source apportionment of heavy metals in agricultural soil through the synthesis of PMF and GeogDetector models
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Contamination assessment and source apportionment of heavy metals in agricultural soil through the synthesis of PMF and GeogDetector models

Fei, Xufeng ; Lou, Zhaohan ; Xiao, Rui ; Ren, Zhouqiao ; Lv, Xiaonan

The Science of the total environment, 2020-12, Vol.747, p.141293-141293, Article 141293 [Periódico revisado por pares]

Elsevier B.V

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